To train the flat model on our datasets, we use an off-the-shelf framework: Flair  [1]}, which achieves the state-of-the-art performance on CoNLL 2003 dataset. Recall that the flat model cannot be directly applied to datasets containing discontinuous mentions. Following the practice in [2]}, we replace the discontinuous mention with the shortest span that fully covers it, and merge overlapping mentions into a single mention that covers both. Different from [2]}, we apply these changes only on the training set, and not on the development and the test sets.
